Every measurement device drifts or changes with time. As a result of this drift, every measurement device must be recalibrated regularly to assure that measurements made by the device remain within a tolerance that is normally defined by specifications of the measurement device. Failure to calibrate the measurement device before it is out of tolerance may have negative consequences, including recalling or questioning all measurements made by the device since the last calibration. A failure to calibrate can also result in erroneous measurements in the field, which can be disastrous in terms of quality, cost, safety, etc. It is therefore highly desirable to calibrate at sufficiently short recalibration intervals.
Although a short recalibration interval is desirable to ensure accurate measurements, a recalibration interval that is shorter than necessary increases calibration frequency thus increasing direct and indirect calibration costs, such as instrument downtime, shipping and associated risks. Currently, the recalibration interval is usually based on past experience with similar devices, and it is selected based on the largest anticipated calibration drift of the measurement device.
The difficulty in selecting an adequately short recalibration interval is exacerbated by the fact that calibration drift occurs in different measurement devices at different rates. Therefore, the recalibration interval of a measurement device is usually statistically determined on the basis of the calibration drift history of a population of similar devices. An interval is then chosen that provides an acceptable likelihood of in-tolerance conditions at calibration. Given the very high cost of out of tolerance conditions at recalibration, the interval must be conservative, and it therefore causes a majority of measurement devices to be calibrated earlier than necessary thereby unnecessarily increasing costs. In addition, the predictive statistical method has no chance of identifying outliers whose behavior deviates significantly from predicted behavior.
There is therefore a need for a system and method that provides an alternative to predictive recalibration interval selection so that a longer recalibration interval can be used without risking out of tolerance conditions at recalibration.